Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.     

Simultaneous Removal of Nitrate and Natural Organic Matter from Drinking Water Using a Hybrid Heterotrophic/Autotrophic/Biological Activated Carbon Bioreactor

Simultaneous removal of nitrate ([Formula: see text]) and natural organic matter (NOM) from drinking water using a hybrid heterotrophic/autotrophic/BAC bioreactor (HHABB) was studied in continuous mode. The HHABB consisted of three compartments: ethanol heterotrophic part, sulfur autotrophic part, and biological activated carbon (BAC)-part (including anoxic and aerobic sections). Experiments were performed with [Formula: see text] concentration 30?mg N/L, [Formula: see text] loading rate 0.72?kg N/m(3)/d, C?:?N ratio 0.53, and three concentrations of NOM (0.6, 2.6, and 5.7?mg C/L). Overall denitrification rate and efficiency of the HHABB were not affected by NOM concentration and were in the suitable ranges of 0.69-0.70?kg N/m(3)/d and 96.0%-97.7%, respectively. NOM removal at concentration 0.6?mg C/L was not efficient because of organic carbon replacement as soluble microbial products. At higher NOM concentrations, total NOM removal efficiencies were 55%-65%, 55%-70%, and 55%-65% for dissolved organic carbon, trihalomethane formation potential, and UV absorbance at 254?nm (UV(254)), respectively. The more efficient compartments of the HHABB for the removal of NOM were the ethanol heterotrophic phase and aerobic BAC-phase. The efficiency of the HHABB in the removal of NOM was considerable, and the effluent dissolved organic carbon and trihalomethane formation potential concentrations were relatively low. This study indicated that the HHABB without the anoxic BAC-phase could be a feasible alternative for simultaneous removal of [Formula: see text] and NOM from drinking water at full scale.     

Elemental composition of particulate matters around Urmia Lake,Iran

Atmospheric particulate matters and their elements were concurrently measured at two sites located in the north and southeast parts of Urmia Lake from January to September 2013. At both sampling sites, average concentrations of total suspended particulate, particles with the aerodynamic diameter of smaller than 10 µm, smaller than 2.5 µm, and smaller than 1 µm were 260 ± 106, 180 ± 73, 30 ± 8, and 25 ± 7 µg m^?3, respectively. The analyzed water soluble ions accounted for approximately 11%–13% mass concentrations of total suspended particulate and 8%–9% of particles smaller than 10 µm, and the sum of the concentrations of the analyzed elements associated with both ranged from 9 to 41 µg m^?3 (6.5%–9.6% in mass) and 7 to 26 µg m^?3 (5.5%–11.3% in mass), respectively. Thus, particulate matter was composed of a complex mixture of minerals such as halite, quartz, gypsum, hexahydrite, and Bassanite.     

Determination of aluminum and zinc in Iranian consumed tea

To determine aluminum and zinc in Iranian consumed tea, 31 tea samples were analysed for Al and Zn concentration of tea leaves and tea infusion. The results show that average concentration of Al and Zn in tea leaves was 326 and 50.7 mg. Kg(-1) respectively in this regard Nemoneh and Shahrzad show the highest and lowest concentration respectively in term of Al, also Debsh and Alkozi follow same situation in Zn concentration. Also the solubility of metals in the first infusion was significantly (Al, Zn: P < 0.01) higher than the second infusion and the solubility in the second infusion was also significantly higher than the third infusion (Al: P < 0.01; Zn: P < 0.05). Al leachate in the first infusion (2 min) for Mosama and Seilan tea was highest and lowest respectively. Also in the second and third infusion (5 and 10 min) Golkis and Nemoneh tea show the highest and lowest figures respectively. On the other hand, data from Zn transfer in tea infusion in the first infusion show that Mosama and Ahmad Atry tea have the highest and lowest leachate percentage respectively, while in the second and third infusion Mosama and Golkis tea follow the same situation. Calculation of percentage 'available' Al and Zn to the human system showed that 1 l of tea can provide 37.2% of the daily dietary intake of Al, the percentage 'available' for absorption in the intestine is only 1.78% for overall mean Al concentration. Also daily dietary intake of Zn was 2.13% while percentage available for absorption in the intestine was 0.72%.     

Spatio-temporal variability of extreme precipitation characteristics under different climatic conditions in Fars province,Iran

Environment, Development and Sustainability - Spatio-temporal variability of extreme precipitation characteristics (EPCs) were analyzed using clustering techniques to establish homogeneous...